Amortized inference and model learning for probabilistic programming
<p>Probabilistic modeling lets us infer, predict and make decisions based on incomplete or noisy data. The goal of <em>probabilistic programming</em> is to automate inference in probabilistic models that are expressed as probabilistic programs---programs that can draw random values...
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| Формат: | Дисертація |
| Мова: | English |
| Опубліковано: |
2019
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